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Image texture analysis using geostatistical information entropy
Aizu Research Cluster for Medical Engineering and Informatics, Research Center for Advanced Information Science and Technology, The University of Aizu Aizu-Wakamatsu, Fukushima, Japan.ORCID iD: 0000-0002-4255-5130
2012 (English)In: Intelligent Systems (IS), 2012 6th IEEE International Conference, IEEE , 2012, 353-356 p.Conference paper (Refereed)Text
Abstract [en]

Extraction of effective features of objects is an important area of research in the intelligent processing of image data. A well-known feature in images is texture which can be used for image description, segmentation and classification. This paper presents a novel texture extraction method using the principles of geostatistics and the concept of entropy in information theory. Experimental results on medical image data have shown the superior performance of the proposed approach over some popular texture extraction methods.

Place, publisher, year, edition, pages
IEEE , 2012. 353-356 p.
Keyword [en]
Image classification; texture feature; geostatistics; indicator kriging; entropy
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-125050DOI: 10.1109/IS.2012.6335160ISBN: 9781467322768 (print)OAI: oai:DiVA.org:liu-125050DiVA: diva2:902708
Conference
The 2012 IEEE Conference on Intelligent Systems, Sofia, Bulgaria, September 6-8, 2012
Available from: 2016-02-12 Created: 2016-02-12 Last updated: 2016-02-22Bibliographically approved

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Pham, Tuan D
Computer Vision and Robotics (Autonomous Systems)

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ReferencesLink to record
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